Research interests
My research area is mainly focused on Machine Learning.
I am specially interested in generative models
Specifically, I have applied copula theory to different subjects such as
- Wind Resource Estimation
- E-Commerce Fraud Detection
- Longitudinal Data Modeling
- Estimation of Distribution Algorithms
Works in the news
- How MIT is training AI language models in an era of quality data scarcity (VentureBeat)
- Method finds hidden warning signals in measurements collected over time (MIT News)
- The real promise of synthetic data (MIT News)
- Auto-tuning data science: New research streamlines machine learning (MIT News)
- System predicts 85 percent of cyber-attacks using input from human experts (MIT News)
- Siting wind farms more quickly, cheaply (MIT News)
Consulting
- AMS Geomatics (2018) Co-Principal investigator
- BE CAE & Test (2021) Principal investigator
- BielGlasses (2017, 18, 19, 20, 21) Research staff
- Ecoembes (2017) Research staff
- EverVest (2014) Principal investigator
- Navmii (2017) Research staff
- PatternEx (2016) Principal investigator
- PixelLabs (2017, 21) Research staff
- Simbiotica (2018) Principal investigator
Competitive Projects
-
EyeOT Smart eyes on digital twins
2022 -- 2024 Agencia Estatal de Investigación (PID2021-128362OB-I00) Co-principal Investigator -
POLLUTWIN High Fidelity Digital Twin of Pollutant Mobile Sources in Cities
2022 -- 2024 Agencia Estatal de Investigación (TED2021-129162B-C22) Research staff -
FotoCaos New computational methods for simulating and optimization of photochemical processes
2019 -- 2021 Comunidad de Madrid (Y2018/EMT-5062) Research staff -
SmartEyes Smart Eyes for Smart Cities
2019 -- 2021 MINECO (RTI2018-098743-B-I00) Co-Principal investigator -
HARAMI Human Activity Recognition with AMbient Intelligence methods
2016 -- 2018 MINECO (TIN2015-69542-C2-1-R) Research staff -
IYELMO PaaS for trading
2011 -- 2014 INNPACTO – IPT-2011-1198-430000 Research staff -
TEDICO controllers design techniques developed with the space of parameters, multirate and fractional order calculus methods
2004 -- 2007 CICYT - DPI2004-05903 Ph.D. student
Postdoc projects and Visiting faculty
Massachusetts Institute of Technology Invited by Dr. Kalyan Veeramachaneni (LIDS)
January, 2018Massachusetts Institute of Technology Invited by Dr. Una-May O'Reilly (CSAIL)
September -- December, 2010 September -- December, 2013-
University of New Mexico Time Series Analysis and Prediction using Copulas and Wavelets. Applications in Control Engineering
January -- August, 2009 José Castillejo research fellowship (JC2008-00421) -
RCC at Harvard Design of Control Systems regarding Stochastic Dependencies
Sept--Dec. 2008, 2009, 2010 RCC at Harvard research fellowship
Selected publications
- S Hernandez-Garcia, A Cuesta-Infante, J.A. Moreno-SanSegundo and A.S. Montemayor: "Deep reinforcement learning for automated search of model parameters: Photo-Fenton wastewater disinfection case study”. Neural Computing and Applications, 35(2): 1379-1394 (2023)
- L. Llopis-Ibor, C. Beltran-Royo, J.J. Pantrigo, A. Cuesta-Infante: "Fast Incremental Learning by Transfer Learning and Hierarchical Sequencing”. Expert Systems with Applications, 212, 118580 (2023)
- L. Xu, A. Cuesta-Infante, L. Berti-Équille, K. Veeramachaneni: "R & R: Metric-guided Adversarial Sentence Generation". Findings of AACL/IJCNLP, 438-452 (2022).
- L. Xu, L. Berti-Equille, A. Cuesta-Infante, K. Veeramachaneni: "In situ Augmentation for Defending Against Adversarial Attacks on Text Classifiers". KDD Workshop on Adversarial Machine Learning (2022). Best paper award.
- Y. Sun, I. Ramírez, A. Cuesta-Infante, K. Veeramachaneni: "Towards Reducing Biases in Combining Multiple Experts Online". IJCAI, 3024-3030 (2021)
- A. Geiger, D. Liu, S. Alnegheimish, A. Cuesta-Infante, K. Veeramachaneni: "TadGAN: Time Series Anomaly Detection Using Generative Adversarial Networks". IEEE Int. Conf. on Big Data, 33-43 (2020)
- I. Ramírez, A. Cuesta-Infante, E. Schiavi, J.J. Pantrigo: "Bayesian Capsule Networks for 3D human pose estimation from single 2D images". Neurocomputing, 379: 67-73 (2020)
- I. Ramírez, A. Cuesta-Infante, J.J. Pantrigo, A.S. Montemayor, et al.: "Convolutional neural networks for computer vision-based detection and recognition of dumpsters". Neural Computing and Applications 32(17): 13203-13211 (2020)
- L. Xu, M. Skoularidou, A. Cuesta-Infante, K. Veeramachaneni: "Modeling Tabular data using Conditional GAN". NeurIPS, 7333-7343 (2019)
- Y. Sun, A. Cuesta-Infante, K. Veeramachaneni: "Learning Vine Copula Models For Synthetic Data Generation". AAAI, 5049-5057 (2019)
- T. Swearingen, W. Drevo, B. Cyphers, A.Ross, A. Cuesta-Infante, K. Veeramachaneni: "ATM: A distributed, collaborative, scalable system for automated machine learning". IEEE Int. Conf. on Big Data, 151-162 (2017)
- I. Arnaldo, A. Cuesta-Infante, A. Arun, M. Lam, C. Bassias, K. Veeramachaneni: "Learning Representations for Log Data in Cybersecurity". Int. Symp. on Cyber Security Cryptography and Machine Learning, 250-268, (2017)
- B. Lacabex, A. Cuesta-Infante, A.S. Montemayor, J.J. Pantrigo: "Lightweight tracking-by-detection system for multiple pedestrian targets". Integrated Computer-Aided Engineering 23(3): 299-311 (2016)
- K. Veeramachaneni, A. Cuesta-Infante, U.M. O'Reilly: "Copula Graphical Models for Wind Resource Estimation". IJCAI 2015: 2646-2654
- J.I. Hidalgo, J.M. Colmenar, J.L. Risco-Martín, A. Cuesta-Infante, E. Maqueda, M. Botella, J.A. Rubio: "Modeling glycemia in humans by means of Grammatical Evolution". Applied Soft Computing 20: 40-53 (2014)
- More at ORCID ( 0000-0002-3328-501X ) , Scopus ( 35955730700 ) , Publons/WoS ( L-3708-2014 ) , Google Scholar ( OQsC-14AAAAJ ) and DBLP ( Q58993442 )
Teaching
since 2016 Universidad Rey Juan Carlos
Computer Security, Information Systems, Developing Video Games with Artificial Intelligence, Video Games Engineering
1999-2015 C.E.S. Felipe II
(Universidad Complutense de Madrid)
Logic Design, Lab. of Computer Engineering, Networks, Computer Security, Data Warehouses and Data Mining
2009 "Problemas de Estructura y Arquitectura de Computadores" (Book in spanish about Computer Architecture assignments)
A. Cuesta, J.I. Hidalgo, J. Lanchares, J.L. Risco.
ISBN: 97-884832259-1-2, Ed. Pearson.
Education
-
Ph.D. in Computer Science UNED
2016 -
Ms.S. in Physics UCM
1998 -
Faculty position Associate Professor
2021